CODEWITHSUNDEEP
pythoncluster-analysissomself-organizing-maps
jartymcfly
jartymcfly

Reputation: 2005

How can I know which cluster of self-organizing map (SOM) an element belongs to in python?

I am new with clustering and neural nets, and I have just started using Self-Organizing Maps (SOM) to perform some clustering. I have a 15 dimensional dataset and I created a som with the next code:

size = 20
from minisom import MiniSom    
som = MiniSom(size, size, 15, sigma=0.3, learning_rate=0.9, random_seed=149)
som.train_random(data, 650000, verbose=True)

And I plotted the som the next way:

plt.figure()
plt.pcolor(som.distance_map().T, cmap='Blues')
plt.colorbar()

plt.show()

My question is: if I have a new 15 dimensional element, how can I know which cluster of the som belongs to?

Upvotes: 2

Views: 2528

Answers (2)

William Herewini
William Herewini

Reputation: 199

I have a feeling that MiniSom has a function implemented for this:

som.winner(*input_data*)

which returns the node that it is closest to.

Upvotes: 1

Mahsa Hassankashi
Mahsa Hassankashi

Reputation: 2139

Best Matching Unit (BMU)

for t in itertools.count():
        i =  np.random.choice(range(len(data)))
        bmu = self.find_bmu(data[i])

Finding the Best Matching Unit

create n x n map with random node vector values

loop while s < StepsMax times

compute what a "close" node means, based on s

compute a learn rate, based on s

pick a random data item

determine the map node closest to data item (BMU)

for-each node close to the BMU

adjust node vector values towards data item

end-loop

SOM - BMU

Upvotes: 1

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